Systems And Methods For Projecting Sample Store Activities That Are Restricted In Non-Sample Stores

ABSTRACT

Systems and methods are provided for estimating non-sampled store activities by applying projection factors to sampled store activities taking into account restrictions on non-sampled store activities. The systems and methods adjust data projection factors for managed healthcare plans that have restrictions in non-sampled stores to prevent unrestricted activity under these plans at sample stores from being projected into non-sample stores where such projected activity would be restricted. Conventional sampled-to-non-sampled store projection factors leading to restricted plan activities are reallocated to non-restricted plan activities in the non-sample store based on the historical ratio of such activities observed in sample stores.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Application SerialNo. 60/947,202, filed Jun. 29, 2007, which is incorporated by referencein its entirety herein.

TECHNICAL FIELD

The presently described subject matter relates generally to systems andmethods for predicting market conditions. The described subject matterin particular relates to devices and techniques for predicting marketdemand for pharmaceutical and other healthcare products.

BACKGROUND

Assignee IMS Health (“IMS”) provides useful market data analysis andinformation solutions for pharmaceutical and healthcare industries. Forexample, IMS provides a pharmaceutical companies improve theeffectiveness of their field sales forces. Xponent now offers expandedtracking capabilities for the long-term care channel and specialtyretail products. Product sales or activity at pharmaceutical stores oroutlets is projected from limited sampled store data.

Some of the projection methodologies used in Xponent are described inpatents and patent applications owned by IMS (e.g., Felthauser et al.U.S. Pat. No. 5,420,786 and U.S. Pat. No. 5,781,893, etc.). Techniquesfor store sizing (i.e., estimating sales volume or activity) are basedon statistical sampling of retail outlet sales assuming, for example,geographical uniformity and homogeneity in the universe of outlets inthe marketplace. Actual sales data from sampled outlets in the universeof outlets is geo-spatially projected or extrapolated to estimate salesat non-sampled outlets. In particular, U.S. Pat. Nos. 5,420,786 and5,781,893, which are incorporated by reference in their entiretiesherein, teach estimating sales activity of a product at an unsampledretail sales outlet using sampled outlets and the distances between thesampled and unsampled outlets. Suitable adjustments to the projectionfactors can made for specialty products for which the assumptions ofgeographical uniformity and homogeneity do not apply. (See e.g., C.Boardman et al. U.S. Pat. No. 7,174,304 B1, which is incorporated byreference in its entirety herein). Further, adjustments can be made forgaps or delays in sample store reporting (“missing suppliers”) using,for example, solutions described in C. Boardman et al. U.S. Patentapplication Publication No. 20060206365 A1, which is incorporated byreference in its entirety herein.

IMS also provides an enhanced information solution PlanTrak™, which isdesigned to address the managed care issues facing pharmaceuticalcompanies. IMS PlanTrak™ provides insights into the influence of managedcare plans, allowing users to pinpoint key managed care organizationsand track the effects of formulary changes and compliance across plans.Compiling data from thousands of retail pharmacies at both the payer andplan levels, PlanTrak makes it easier for users to design the bestapproaches, validate managed care rebates, and target plans with thebest potential. Like Xponent, PlanTrak applies suitable statisticalprojection factors to data from sampled stores and outlets to obtainestimates of activity at non-sampled stores or outlets.

In practice, incoming market data from reporting outlets (e.g., for acurrent week forecast) is combined with previously calculated projectionfactors to create new projection factors for the current week. The newprojection factors are used to project the product sales for the samplestores. Based on both the reported and projected sales data for thesample stores, the product level distribution factors are computed.These product level distribution factors are used to project theprescription sales for all non-sample outlets.

A drawback of existing projection methodologies is that they do notdistinguish or account for managed care plan restrictions on store oroutlet type. For example, managed care organizations may restrict theirmembers to have prescriptions filled only at certain pharmacies. Theconventional projection methodologies do not consider the effect of planrestrictions on use of non-sample outlets by their members. Using theconventional projection methodologies, it is possible to inappropriatelyproject “non-restricted” activity (e.g., prescriptions) in sample storesor outlets into non-sample stores or outlets in which such activitywould be restricted or not allowed under the managed care plans.

Consideration is now being given to improving devices and techniques toproperly account for store-by-store plan restrictions in the informationsolutions for pharmaceutical and healthcare industries.

SUMMARY

Systems and methods are provided for market data analysis and marketactivity estimation in the pharmaceutical and healthcare industries. Thesystems and methods account for store-by-store restrictions (e.g., store-by-store activity restrictions under managed care plans). The systemsand methods are collectively referred to hereinafter as “Restricted Plansolutions.”

In some embodiments, the Restricted Plan solutions project marketactivity data from sample stores or outlets to estimate activity atnon-sample stores taking into account managed care plan restrictions.The Restricted Plan solutions adjust data projection factors for managedcare plans that have restrictions in non-sample outlets, to preventunrestricted activity under these plans at sample stores from beingprojected into non-sample stores/outlets where such activity would berestricted. The projection methodology does not cause any variation inestimated total prescriptions (“TRx”) at the product or prescriberlevels. Projection factors, which under conventional methodology wouldbe associated with restricted plan activities in non-sample outlets, arere-assigned or reallocated to non-restricted plan activities innon-sample outlets. The reassignment or reallocation of projectedrestricted plan activities to non-restricted activities may be based onthe historical ratio of such activities observed in sample prescriptions(Rxs).

The Restricted Plan solutions may provide users with accuraterepresentations of managed care organization prescription activities,enabling better decision making.

Some embodiments include a procedure for projecting sample storeactivities that are restricted in non-sample stores includingidentifying restricted activities data within a projection, therestricted activities data indicating activities disallowed at nonsamplestores; removing the restricted activities data from the projection;generating replacement activities data for the nonsample stores; andreassigning the replacement activities data to non-restricted plansbased at least in part on factors applied to nonrestricted activities atnonsample stores. In some embodiments, the activities may includescripts purchases. In others, the estimated total activities may remainconstant. The procedure may further include reassigning the replacementactivities data based at least in part on historical ratios of sampled,restricted activities to sampled, non-restricted activities.

Some embodiments include a procedure for projecting sample storeactivities that are restricted in non-sample stores includingdetermining restricted outlet-plan combinations applicable in a marketregion; generating exclusion lists of nonsample stores; generatingrestricted plan allocation data; generating restricted plan adjustments(RPA) factors data; selecting, from a current week sample TRxs datafile, a first group including scripts associated with a restricted planand a second group including scripts not associated with a restrictedplan; appending RPA factors to one or more scripts in the first group;and adjusting missing supplier records. Some embodiments further includegenerating reverse roster data identifying which outlets a restrictedplan is not allowed to fill prescriptions for. Others include generatingthe roster data by combining the current month next generationprescription services universe, current month plan rosters forrestricted plans, and coverage area. Some embodiments include summing,at the outlet-product-plan level, non-missing supplier weights to createRPA factors

Some embodiments include a procedure for projecting sample storeactivities that are restricted in non-sample stores includingdetermining restricted outlet-plan combinations; exploding anexclusion/inclusion parameter files; creating a restricted planallocation file; appending allocations to weight files; creating factorfiles from the weight files; transforming factors; splitting samplefile; applying factors to rxs; splitting missing supplier weights; andappending missing supplier weights to sample rxs.

Some embodiments include an article of manufacture including a computerreadable medium having computer executable instructions embodiedtherein, the computer instructions for projecting sample storeactivities that are restricted in non-sample stores, the computerexecutable instructions causing a computer system to perform theprocedure including identifying restricted activities data within aprojection, the restricted activities data indicating activitiesdisallowed at nonsample stores; removing the restricted activities datafrom the projection; generating replacement activities data for thenonsample stores; and reassigning the replacement activities data tonon-restricted plans based at least in part on factors applied tononrestricted activities at nonsample stores. In some embodiments, theactivities include scripts purchases. In others, the estimated totalactivities remains constant. Some embodiments include reassigning thereplacement activities data based at least in part on historical ratiosof sampled, restricted activities to sampled, non-restricted activities.

BRIEF DESCRIPTION OF THE DRAWINGS AND APPENDICES

Further features of the described subject matter, its nature, andvarious advantages will be more apparent from the following detaileddescription of the preferred embodiments and the accompanying drawings,wherein like reference characters represent like elements throughout,and in which:

FIG. 1 is a block diagram of an exemplary prescription activityestimation process based on the Restricted Plan projection methodology,in accordance with the principles of the presently described subjectmatter;

FIG. 2 illustrates an exemplary input original activity reporting tableand a resulting output Restricted Plan Adjustments (RPA) table createdby the prescription activity estimation process of FIG. 1, in accordancewith the principles of the presently described subject matter;

APPENDIX A is a list of exemplary input and output data files of theprescription activity estimation process of FIG. 1, in accordance withthe principles of the presently described subject matter;

APPENDIX B provides Technical Specifications for an exemplaryimplementation of the prescription activity estimation process of FIG.1, in accordance with the principles of the presently described subjectmatter;

APPENDIX C provides functional and system specifications for anexemplary product implementation of the prescription activity estimationprocess of FIG. 1 in existing projection methodology systems (e.g.,Missing Data Supplier projection methodology system, Appendix D), inaccordance with the principles of the presently described subjectmatter; and

APPENDIX D provides functional and system specifications for anexemplary Missing Data Supplier projection methodology product, whichmay be used as a base for implementation of the prescription activityestimation process of FIG. 1, in accordance with the principles of thepresently described subject matter. The Missing Data Supplier projectionmethodology product may be based on solutions that are described, forexample, in C. Boardman et al. U.S. Patent application Publication No.20060206365 A1.

DETAILED DESCRIPTION

Solutions (hereinafter Restricted Plan solutions) are provided foraccurately estimating market activity based on sample store activitydata.

The restricted plan solutions may be implemented in conjunction withother solutions for estimating pharmaceutical sales activity including,for example, Xponent and Plan Track, and solutions described in C.Boardman et al. U.S. Patent publication No. 20060190288. APPENDIX Dshows functional and system specifications for an exemplary Missing DataSupplier projection methodology product, which may be used as a base forimplementation of the Restricted Plan solutions. APPENDIX C providesfunctional and system specifications for an exemplary productimplementation of Restricted Plan solutions in the Missing Data Supplierprojection methodology system of Appendix D). The accompanyingappendices are provided for illustrative purposes only, and unlessexplicitly specified, are not intended to limit the scope of thedescribed subject matter.

The Restricted Plan solutions properly account for store-by-storeactivity restrictions (e.g., store -by-store activity restrictions undermanaged health care plans) in projecting store activity from one storeto another. A managed health care plan is considered restricted if thepatients who use that plan are limited to purchasing scripts fromspecific pharmacies included on that plan's roster. The inventiveRestricted Plan solutions use a projection methodology that limits orrestricts the non-sample outlets into which sample outlet activities areprojected. The Restricted Plan projection methodology removes planactivities, which would be restricted or not allowed in the non-sampleoutlets, from the projections. The removed activities areproportionately reassigned or reallocated to non-restricted planactivities in the non-sample outlets. “Cloned” records are created basedon the disallowed original sample script. Factors made from weights witha non-roster non-sample outlet that are applied to the sample scriptswith a restricted plan are reallocated to non-restricted plans.

In this manner, the Restricted Plan projection methodology does notcause any variation in the estimated total scripts or prescriptions(“TRx”) at the product or prescriber levels.

In exemplary implementations, the Restricted Plan projection methodologyadjusts down the projection factor on sample scripts with the restrictedplan. The amount of downward adjustment of projection factor is thenreallocated to ‘cloned’ scripts associated with a different plan (whichis not restricted in the non-sample store). A cloned script is aprojected script with identical attributes to a sample script with therestricted plan (it would not be counted as raw). The allocationpercentages may be determined on a historical basis. After reallocation,the product level (i.e. CMF7/USC descriptor-level) and doctor-levelprojections will add up to the same number of scripts. However, theplan-level projections will change because of the reallocation of therestricted plan scripts.

FIG. 1 shows an exemplary prescription activity estimation process 100based on the Restricted Plan projection methodology. Process 100 may berun at suitable times (e.g., weekly) to obtain estimates of prescriptionactivities in a market region based on sample store data received duringa period. The input files for the prescription activity estimationprocess 100 may include Store universe files (e.g., Next GenerationPrescription Services (NGPS) store universe files), Roster files, plancoverage files, prior weeks of sample TRxs, prior weeks of weights,current week sample TRxs, Parameter files, plan inclusion lists, andplan exclusion lists. APPENDIX A is a list of exemplary input and outputdata files of the prescription activity estimation process 100.

Prior to the current week sample store data receipt, at step 110, adetermination is made of all restricted outlet-plan combinationsapplicable in the market region. A reverse roster identifying whichoutlets a restricted plan is not allowed to fill prescriptions iscreated. The reverse roster may be limited to restricted plans and tooutlets within the plans' coverage area. Such a reverse roster may becreated by combining the current month NGPS Universe, current month planrosters for restricted plans, and coverage area.

At step 120, exclusion lists of nonsample stores for specific plans aredeveloped. At step 130, restricted plan allocation files are created.The allocation file identifies which non-restricted plans are ablereceive the restricted plan's taken away TRxs, and what proportion ofthe total TRxs each non-restricted plan should receive. In practice, theallocation file can be created, for example, by combining X weeks (e.g.,X=4) of weights and sample scripts to obtain a dataset at the sampleoutlet-non sample outlet- product-plan level file. The restricted plandata comes from the sample TRxs. A “Weighted Rx” value may be calculatedbased on the number of sample scripts and value of the weight calculatedas: Weighted TRxs=(Weight*Sum of Rxs). The combination is limited torecords corresponding to those non-sample outlets that appear in thereverse roster. Additionally, records are removed where the restrictedplan is a New plan. Further, records are also removed when the New Planis on the plan exclusion list. Conversely, if a restricted plan is onthe plan inclusion list, then it is allowed to be reallocated to newplans with model types identified on the plan inclusion list. Thislimitation is expected to affect a few of the common restricted plans.The allocation percentages may be calculated, for example, as:Allocation %=Weighted Rxs/Total Weighted Rxs, where Total Weighted Rxsis the Weighted Rxs rolled up to the Sample Outlet-NS Outlet-Productlevel. Records may be removed where the Allocation % is less than acutoff X % (e.g., 0.5%). The Allocation % may be then recalculated afterthe below cutoff records are removed to maintain a 100% allocation atthe Outlet-NS Outlet-Product level.

Xponent PlanTrak has outlet-plan level factors. In contrast, process 100may create outlet-product-plan level factors for those products andoutlets that need them. Others use normal outlet-product level factors.To obtain these factors, first at step 140, the Codes and Allocationfile is combined with the store weights file (e.g., distance weights).The allocation file has 100% allocation for each weight record. If thenon-sample outlet in the weight file has a restricted plan, but noallocation record is found then the restricted plan is identified as NewPlan=Plan X. Plan and the allocation % may be set to =100%. Plan X maybe a parameter e.g., =‘8888880001’. When combined, the allocation filedistributes the original weight across the allowable non-restrictedplans.

Next at step 150, a restricted plan adjustments (RPA) factors file iscreated. Non-missing supplier weights are summed at theoutlet-product-plan level to create RPA factors. Some of the plans willbe blank—this factor will be for the factor that comes from non-sampleoutlets with no restrictions. The RPA factors file is different from theexisting, unmodified, factor file, which is still used in a separatestream.

During or after the current week sample store data receipt, at step 160,the current week sample TRxs data file is split and RPA factors areappended. The current week sample TRxs data file is split in two groupshaving a restricted plan and not having a restricted plan, respectively(e.g., Group 1 and Group 2). RPA adjusted factors are appended to theGroup 1 scripts at the sample outlet plan level. Conversely, normalnon-adjusted factors are appended to Group 2 the Group 1 scripts at thesample outlet plan level. It is noted that the Group 1 scripts also gothrough normal processing, but the normal processing records are backedout in the RPA table (step 180).

At step 170 missing supplier records are adjusted. Missing supplier (MS)weights and non -missing supplier factors are appended to the splitfiles and output to an RPA table (step 180). To adjust missing supplierrecords, missing supplier weights are split in two categories Group Aand Group B, which correspond to non sample outlets which have and donot have a restricted plan, respectively. No adjustments are made tomissing supplier records for Group A records. If a Group B weight isused to create a “borrowed” or cloned script, which is not dropped inthe cutoff/rounding procedure, the restricted plan on the record ischanged to reflect the new non-restricted plan. If the plan is sochanged, the PBM BIN ID is set to null to prevent the particular recordfrom having its prescriber entry changed in any down stream missingsupplier adjustment processes. The results of step 170 are output to anRPA table at step 180.

FIG. 2 shows an exemplary output RPA table 300 and an exemplary originalreporting Table 200. As shown, Table 200 contains an originalprescription record 212 for product “SneezeAlot” filled at sample outlet“SS” under Plan C. However, plan C may be restricted in non-sampleoutlet NN, which is associated with sample outlet SS, After process 100,RPA table 200 includes a negative “back out” record 312 to remove therestricted script 212 with the original unadjusted factor. Further, RPAtable 300 includes a positive “feed back” record 314 that maintains theoriginal characteristics, including the restricted plan C. This record314 does not need to have an adjusted plan as it is used for orassociated with non-sample outlets NN that not have restrictions underPlan C. RPA table 300 also includes a positive “feed back” records 316and 318 that are used for or associated with non-sample outlets NN thatdo have restrictions under Plan C. These records for have adjusted plans(e.g., Plan A and Plan B, respectively) indicating the reallocation ofthe projection of restricted script 212 to non restricting plans A andB.

Appendix B lists Technical Specifications for an exemplaryimplementation of prescription activity estimation process 100. In theexemplary implementation, Restricted Plans and other special cases arereallocated in the retail channel. All reference files and input filesuse retail data. Rosters and geographies (coverage areas) are availablefor all restricted plans in a mainframe file. Weight files are createdand capped. Certain plans are excluded from reallocation. These are thesame across all outlets and are made available in a parameter file(Parameter File). Restricted plans with certain model types are allowedto be reallocated to specific model types. These are the same across alloutlets and are be available in a parameter file (Parameter File). Allappropriate cross-references will be applied based on current weekfiles.

In accordance with the presently described subject matter, software(i.e., instructions) for implementing the aforementioned Restricted Plansolutions/devices and techniques (algorithms) can be provided oncomputer-readable media. It will be appreciated that each of theprocedures (described above in accordance with this described subjectmatter), and any combination thereof, can be implemented by computerprogram instructions. These computer program instructions can be loadedonto a computer or other programmable apparatus to produce a machinesuch that the instructions, which execute on the computer or otherprogrammable apparatus, create means for implementing the functions ofthe aforementioned systems and methods. These computer programinstructions can also be stored in a computer-readable memory that candirect a computer or other programmable apparatus to function in aparticular manner such that the instructions stored in thecomputer-readable memory produce an article of manufacture includinginstruction means, which implement the functions of the aforementionedsystems and methods. The computer program instructions can also beloaded onto a computer or other programmable apparatus to cause a seriesof operational steps to be performed on the computer or otherprogrammable apparatus to produce a computer implemented process suchthat the instructions which execute on the computer or otherprogrammable apparatus provide steps for implementing the functions ofthe aforementioned systems and methods. It will also be understood thatthe computer-readable media on which instructions for implementing theaforementioned systems and methods are be provided include, withoutlimitation, firmware, microcontrollers, microprocessors, integratedcircuits, ASICS, and other available media.

In some embodiments, one or more computer components, working togetherwith said software or instructions, may be provided to implement thedescribed subject matter. A first example may include one or more of anidentifying component for identifying restricted activities data withina projection, the restricted activities data indicating activitiesdisallowed at nonsample stores, a removal component for removing therestricted activities data from the projection, a generation componentfor generating replacement activities data for the nonsample stores, anda reassignment component for reassigning the replacement activities datato non-restricted plans based at least in part on factors applied tononrestricted activities at nonsample stores.

A second example may include one or more of a combination determinationcomponent for determining restricted outlet-plan combinations applicablein a market region, an exclusion list component for generating exclusionlists of nonsample stores, a restricted allocation data component forgenerating restricted plan allocation data, a plan adjustments componentfor generating restricted plan adjustments (RPA) factors data, aselection component for selecting, from a current week sample TRxs datafile, a first group including scripts associated with a restricted planand a second group including scripts not associated with a restrictedplan, an appending component for appending RPA factors to one or morescripts in the first group, an adjustment component for adjustingmissing supplier records, a reverse roster data component for generatingreverse roster data identifying which outlets a restricted plan is notallowed to fill prescriptions for, a combination component forgenerating the roster data by combining the current month nextgeneration prescription services universe, current month plan rostersfor restricted plans, and coverage area, a summing component forsumming, at the outlet-product-plan level, non-missing supplier weightsto create RPA factors

A third example may include one or more of a combination determinationcomponent for determining restricted outlet-plan combinations, anexplosion component for exploding an exclusion/inclusion parameterfiles, a plan application component for creating a restricted planallocation file, a weight files component for appending allocations toweight files, a factor files component for creating factor files fromthe weight files, a factor transformation component for transformingfactors, a splitting component for splitting sample file, a factorapplication component for applying factors to rxs, a missing weightssplitting component for splitting missing supplier weights, and asupplier weights application component for appending missing supplierweights to sample rxs.

The foregoing merely illustrates the principles of the disclosed subjectmatter. Various modifications and alterations to the describedembodiments will be apparent to those skilled in the art in view of theteachings herein. It will thus be appreciated that those skilled in theart will be able to devise numerous techniques which, although notexplicitly described herein, embody the principles of the disclosedsubject matter and are thus within the spirit and scope thereof.

1. A method for projecting sample store activities that are restrictedin non-sample stores, comprising: identifying restricted activities datawithin a projection, the restricted activities data indicatingactivities disallowed at nonsample stores; removing the restrictedactivities data from the projection; generating replacement activitiesdata for the nonsample stores; and reassigning the replacementactivities data to non-restricted plans based at least in part onfactors applied to nonrestricted activities at nonsample stores.
 2. Themethod of claim 1, wherein the activities include scripts purchases. 3.The method of claim 1, wherein the estimated total activities remainsconstant.
 4. The method of claim 1, wherein reassigning the replacementactivities data is based at least in part on historical ratios ofsampled, restricted activities to sampled, non-restricted activities. 5.A method for projecting sample store activities that are restricted innon-sample stores, comprising: determining restricted outlet-plancombinations applicable in a market region; generating exclusion listsof nonsample stores; generating restricted plan allocation data;generating restricted plan adjustments (RPA) factors data; selecting,from a current week sample TRxs data file, a first group includingscripts associated with a restricted plan and a second group includingscripts not associated with a restricted plan; appending RPA factors toone or more scripts in the first group; and adjusting missing supplierrecords.
 6. The method of claim 5, further comprising: generatingreverse roster data identifying which outlets a restricted plan is notallowed to fill prescriptions for.
 7. The method of claim 6, furthercomprising: generating the roster data by combining the current monthnext generation prescription services universe, current month planrosters for restricted plans, and coverage area.
 8. The method of claim5, further comprising: summing, at the outlet-product-plan level,non-missing supplier weights to create RPA factors
 9. a method forprojecting sample store activities that are restricted in non-samplestores, comprising: determining restricted outlet-plan combinations;exploding an exclusion/inclusion parameter files; creating a restrictedplan allocation file; appending allocations to weight files; creatingfactor files from the weight files; transforming factors; splittingsample file; applying factors to rxs; splitting missing supplierweights; and appending missing supplier weights to sample rxs.
 10. Anarticle of manufacture comprising a computer readable medium havingcomputer executable instructions embodied therein, the computerinstructions for projecting sample store activities that are restrictedin non-sample stores, the computer executable instructions causing acomputer system to perform the steps comprising: identifying restrictedactivities data within a projection, the restricted activities dataindicating activities disallowed at nonsample stores; removing therestricted activities data from the projection; generating replacementactivities data for the nonsample stores; and reassigning thereplacement activities data to non-restricted plans based at least inpart on factors applied to nonrestricted activities at nonsample stores.11. The article of manufacture of claim 10, wherein the activitiesinclude scripts purchases.
 12. The article of manufacture of claim 10,wherein the estimated total activities remains constant.
 13. The articleof manufacture of claim 10, wherein reassigning the replacementactivities data is based at least in part on historical ratios ofsampled, restricted activities to sampled, non-restricted activities.